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AR Point &Click: An Interface for Setting Robot Navigation Goals

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Social Robotics (ICSR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13817))

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Abstract

This paper considers the problem of designating navigation goal locations for interactive mobile robots. We investigate a point-and-click interface, implemented with an Augmented Reality (AR) headset. The cameras on the AR headset are used to detect natural pointing gestures performed by the user. The selected goal is visualized through the AR headset, allowing the users to adjust the goal location if desired. We conduct a user study in which participants set consecutive navigation goals for the robot using three different interfaces: AR Point &Click, Person Following and Tablet (birdeye map view). Results show that the proposed AR Point &Click interface improved the perceived accuracy, efficiency and reduced mental load compared to the baseline tablet interface, and it performed on-par to the Person Following method. These results show that the AR Point &Click is a feasible interaction model for setting navigation goals.

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Notes

  1. 1.

    Due to the COVID-19 pandemic, no external participants could be recruited. This study has been approved by the Monash University Human Research Ethics Committee (Application ID: 27685)

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Acknowledgement

This project was supported by the Australian Research Council (ARC) Discovery Project Grant DP200102858.

Author information

Authors and Affiliations

  1. Monash University, Clayton, Australia

    Morris Gu

  2. University of Victoria, Victoria, Canada

    Elizabeth Croft

  3. Deakin University, Burwood, Australia

    Akansel Cosgun

Authors
  1. Morris Gu
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  2. Elizabeth Croft
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  3. Akansel Cosgun
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Corresponding author

Correspondence to Morris Gu .

Editor information

Editors and Affiliations

  1. University of Florence, Florence, Italy

    Filippo Cavallo

  2. Qatar University, Doha, Qatar

    John-John Cabibihan

  3. University of Florence, Florence, Italy

    Laura Fiorini

  4. University of Florence, Florence, Italy

    Alessandra Sorrentino

  5. Wichita State University, Wichita, KS, USA

    Hongsheng He

  6. Qingdao University, Qingdao, China

    Xiaorui Liu

  7. National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan

    Yoshio Matsumoto

  8. National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

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Gu, M., Croft, E., Cosgun, A. (2022). AR Point &Click: An Interface for Setting Robot Navigation Goals. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13817. Springer, Cham. https://doi.org/10.1007/978-3-031-24667-8_4

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  • DOI: https://doi.org/10.1007/978-3-031-24667-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24666-1

  • Online ISBN: 978-3-031-24667-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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